This study collected epidemic data of COVID-19 in Zhengzhou from January 1 to January 20 in 2022. The epidemiological characteristics of the local epidemic in Zhengzhou High-tech Zone caused by the SARS-CoV-2 Delta variant were analyzed through epidemiological survey and big data analysis, which could provide a scientific basis for the prevention and control of the Delta variant. In detail, a total of 276 close contacts and 599 secondary close contacts were found in this study. The attack rate of close contacts and secondary close contacts was 5.43% (15/276) and 0.17% (1/599), respectively. There were 10 confirmed cases associated with the chain of transmission. Among them, the attack rates in close contacts of the first, second, third, fourth and fifth generation cases were 20.00% (5/25), 17.86% (5/28), 0.72% (1/139) and 14.81% (4/27), 0 (0/57), respectively. The attack rates in close contacts after sharing rooms/beds, having meals, having neighbor contacts, sharing vehicles with the patients, having same space contacts, and having work contacts were 26.67%, 9.10%, 8.33%, 4.55%, 1.43%, and 0 respectively. Collectively, the local epidemic situation in Zhengzhou High-tech Zone has an obvious family cluster. Prevention and control work should focus on decreasing family clusters of cases and community transmission.
Humans ; SARS-CoV-2 ; COVID-19 ; Epidemics ; Incidence

Objective: To explore the epidemiological characteristic of a COVID-19 outbreak caused by 2019-nCoV Omicron variant BF.7 and other provinces imported in Shenzhen and analyze transmission chains and characteristics. Methods: Field epidemiological survey was conducted to identify the transmission chain, analyze the generation relationship among the cases. The 2019-nCoV nucleic acid positive samples were used for gene sequencing. Results: From 8 to 23 October, 2022, a total of 196 cases of COVID-19 were reported in Shenzhen, all the cases had epidemiological links. In the cases, 100 were men and 96 were women, with a median of age, M (Q₁, Q₃) was 33(25, 46) years. The outbreak was caused by traverlers initial cases infected with 2019-nCoV who returned to Shenzhen after traveling outside of Guangdong Province.There were four transmission chains, including the transmission in place of residence and neighbourhood, affecting 8 persons, transmission in social activity in the evening on 7 October, affecting 65 persons, transmission in work place on 8 October, affecting 48 persons, and transmission in a building near the work place, affecting 74 persons. The median of the incubation period of the infection, M (Q₁, Q₃) was 1.44 (1.11, 2.17) days. The incubation period of indoor exposure less than that of the outdoor exposure, M (Q₁, Q₃) was 1.38 (1.06, 1.84) and 1.95 (1.22, 2.99) days, respcetively (Wald χ²=10.27, P=0.001). With the increase of case generation, the number and probability of gene mutation increased. In the same transmission chain, the proportion of having 1-3 mutation sites was high in the cases in the first generation. Conclusions: The transmission chains were clear in this epidemic. The incubation period of Omicron variant BF.7 infection was shorter, the transmission speed was faster, and the gene mutation rate was higher. It is necessary to conduct prompt response and strict disease control when epidemic occurs.
Male ; Humans ; Female ; SARS-CoV-2 ; COVID-19/epidemiology* ; Disease Outbreaks ; Epidemics ; China/epidemiology*

Objective: To explore the feasibility of moving epidemic method (MEM) in the assessment of seasonal influenza (influenza) activity intensity from the perspective of urban agglomeration, assess influenza activity intensity in the Beijing-Tianjin-Hebei region from 2019 to 2021 and evaluate the reliability of surveillance data and the effectiveness of the MEM model application. Methods: The weekly reported incidence rate (IR) of influenza and the percentage of influenza-like illness (ILI%) from 2011-2021 in Beijing-Tianjin-Hebei region were collected to establish MEM models respectively. The model fitting effect and the reliability of the two data were evaluated for the purpose of establishing an optimal model to assess the influenza activity intensity in Beijing-Tianjin-Hebei region from 2019-2021. A cross-validation procedure was used to evaluate the performance of the models by calculating the Youden's index, sensitivity and specificity. Results: The MEM model fitted with weekly ILI% had a higher Youden's index compared with the model fitted with weekly IR at both Beijing-Tianjin-Hebei region level and provincial level. The MEM model based on ILI% showed that the epidemic threshold in Beijing-Tianjin-Hebei region during 2019-2020 was 4.42%, the post-epidemic threshold was 4.66%, with medium, high and very high intensity thresholds as 5.38%, 7.22% and 7.84%, respectively. The influenza season during 2019-2020 had 10 weeks (week 50 of 2019 to week 7 of 2020). The influenza season started in week 50 of 2019, and the intensity fluctuated above and below medium epidemic level for six consecutive weeks. The high intensity was observed in week 4 of 2020, the threshold of very high intensity was excessed in week 5, and the intensity gradually declined and became lower than the threshold at the end of the influenza season in week 8. The epidemic threshold was 4.29% and the post-epidemic threshold was 4.35% during 2020-2021. Influenza activity level never excessed the epidemic threshold throughout the year, and no epidemic period emerged. Conclusions: The MEM model could be applied in the assessment of influenza activity intensity in Beijing-Tianjin-Hebei region, and the use of ILI% to assess influenza activity intensity in this region was more reliable than IR data. Influenza activity intensity in Beijing-Tianjin-Hebei region was higher during 2019-2020 but significantly lower in 2020-2021.
Humans ; Beijing/epidemiology* ; Influenza, Human/epidemiology* ; Seasons ; Reproducibility of Results ; Epidemics ; China/epidemiology*

OBJECTIVE: To analyze the global epidemic status of the Ebola virus disease (EVD) and assess the importation risk into China. METHODS: Data from World Health Organization reports were used. We described the global epidemic status of EVD from 1976-2021, and assessed and ranked the importation risk of EVD from the disease-outbreaking countries into China using the risk matrix and Borda count methods, respectively. RESULTS: From 1976-2021, EVD mainly occurred in western and central Africa, with the highest cumulative number of cases (14,124 cases) in Sierra Leone, and the highest cumulative fatality rate (85%) in the Congo. Outbreaks of EVD have occurred in the Democratic Republic of the Congo and Guinea since 2018. The importation risk into China varies across countries with outbreaks of disease. The Democratic Republic of the Congo had an extremely high risk (23 Borda points), followed by Guinea and Liberia. Countries with a moderate importation risk were Nigeria, Uganda, Congo, Sierra Leone, Mali, and Gabon, while countries with a low importation risk included Sudan, Senegal, and Co^te d'Ivoire. CONCLUSION China is under the risk of EVD importation with the globalization and severe epidemic status of EVD. Key attention need to be paid to the Democratic Republic of the Congo, Guinea, and Liberia. Therefore, it is necessary to prevent and prepare in advance for importation risk in China.
Humans ; Hemorrhagic Fever, Ebola/prevention & control* ; Epidemics ; Disease Outbreaks/prevention & control* ; Guinea/epidemiology* ; Sierra Leone/epidemiology* ; China/epidemiology*

At the end of 2022, the World Health Organization reported an increase in group A Streptococcus (GAS) infections, such as scarlet fever, in multiple countries. The outbreak primarily affected children under 10 years old, and the number of deaths was higher than anticipated, causing international concern. This paper reviews the current state of the GAS disease outbreak, its causes, and response measures. The authors aim to draw attention from clinical workers in China and increase their awareness and vigilance regarding this epidemic. Healthcare workers should be aware of the potential epidemiological changes in infectious diseases that may arise after the optimization of control measures for coronavirus disease 2019 to ensure children's health.
Child ; Humans ; Streptococcus pyogenes ; COVID-19/epidemiology* ; Streptococcal Infections/epidemiology* ; Scarlet Fever/epidemiology* ; Epidemics ; Disease Outbreaks

OBJECTIVES: To study the clinical features of children with febrile seizures after Omicron variant infection. METHODS: A retrospective analysis was performed on the clinical data of children with febrile seizures after Omicron variant infection who were admitted to the Department of Neurology, Children's Hospital Affiliated to the Capital Institute of Pediatrics, from December 1 to 31, 2022 (during the epidemic of Omicron variant; Omicron group), and the children with febrile seizures (without Omicron variant infection) who were admitted from December 1 to 31, in 2021 were included as the non-Omicron group. Clinical features were compared between the two groups. RESULTS: There were 381 children in the Omicron group (250 boys and 131 girls), with a mean age of (3.2±2.4) years. There were 112 children in the non-Omicron group (72 boys and 40 girls), with a mean age of (3.5±1.8) years. The number of children in the Omicron group was 3.4 times that in the non-Omicron group. The proportion of children in two age groups, aged 1 to <2 years and 6-10.83 years, in the Omicron group was higher than that in the non-Omicron group, while the proportion of children in two age groups, aged 4 to <5 years and 5 to <6 years, was lower in the Omicron group than that in the non-Omicron group (P<0.05).The Omicron group had a significantly higher proportion of children with cluster seizures and status convulsion than the non-Omicron group (P<0.05). Among the children with recurrence of febrile seizures, the proportion of children aged 6-10.83 years in the Omicron group was higher than that in the non-Omicron group, while the proportion of children aged 3 years, 4 years, and 5 years in the Omicron group was lower than that in the non-Omicron group (P<0.05). CONCLUSIONS Children with febrile seizures after Omicron variant infection tend to have a wider age range, with an increase in the proportion of children with cluster seizures and status convulsion during the course of fever.
Male ; Female ; Humans ; Child ; Infant ; Child, Preschool ; Seizures, Febrile/etiology* ; Retrospective Studies ; Seizures ; Fever ; Epidemics ; Epilepsy, Generalized

OBJECTIVES: To study the differences in the clinical features of children with coronavirus disease 2019 (COVID-19) in different age groups during the epidemic of Omicron variant. METHODS: A retrospective analysis was performed on the clinical data of 211 children with COVID-19 who were admitted to the Department of General Pediatrics, Zhongshan People's Hospital, from December 9, 2022 to January 8, 2023. According to their age, they were divided into 4 groups: 1 month-<1 year (n=84), 1-<3 years group (n=64), 3-<5 years (n=29), and ≥5 years (n=34). The above groups were compared in terms of general status, clinical features, ancillary examination results, treatment, and outcome. RESULTS: The children aged <3 years accounted for 70.1% (148/211) of all hospitalized children with COVID-19, and the 3-<5 years group and the ≥5 years group had a significantly higher proportion of children with underlying diseases than the 1 month-<1 year group and the 1-<3 years group (P<0.05). Compared with the other three groups, the 1 month-<1 year group had significantly higher incidence rates of dyspnea, nasal congestion/nasal discharge, diarrhea and significantly lower incidence rates of convulsion and nervous system involvement (P<0.05). Moreover, compared with the other three groups, the 1 month-<1 year group had significantly higher incidence rates of increases in bile acid and creatine kinase isoenzyme and significantly lower incidence rates of decreased platelet count, increased neutrophil percentage, and decreased lymphocyte percentage (P<0.05). The 1 month-<1 year group had a significantly higher incidence rate of mild COVID-19 than the 1-<3 years group and a significantly lower incidence rate of severe/critical COVID-19 than the other three groups (P<0.05). Compared with the other three groups, the 1 month-<1 year group had a significantly higher proportion of children receiving oxygen inhalation therapy (P<0.05). CONCLUSIONS Children with COVID-19 in different age groups have different clinical features during the epidemic of Omicron variant, especially between the children aged 1 month to <1 year and those aged ≥1 year.
Humans ; Child ; COVID-19 ; Retrospective Studies ; SARS-CoV-2 ; Epidemics

Medical supply is a key resource for responding to public health emergencies and maintaining people's lives and health. As the medical equipment management department, the medical devices department is mainly responsible for the procurement, supply, technical support, management and coordination of medical equipment and medical consumables, playing an important role in epidemic prevention and control. Through the analysis of the expansion cases of designated hospitals, the experience of emergency management of medical equipment has been accumulated, which has strong practicability and replicability.
Humans ; Public Health ; Emergencies ; Hospitals ; Epidemics

Human bocavirus is a novel pathogen first detected in respiratory tract samples in 2005. People of different ages can be infected by human bocavirus. Children are the susceptible population, especially the infants aged from 6-24 months old. The epidemic season varies in different regions due to the differences in climate and geographical location, and it mainly occurs in autumn and winter. It's demonstrated that human bocavirus-1 is closely related to respiratory system diseases and even causes life-threatening critical illness. Also, the severity of symptom is positively correlated with viral load. Co-infections between human bocavirus-1 and other viruses often present high frequency occurrence. Human bocavirus-1 interferes immune function of host by inhibiting interferon secrete pathway. Currently, it remains limited knowledge and understanding of the roles of human bocavirus 2-4 in diseases, but the gastrointestinal diseases should be paid more attention. Detection of human bocavirus DNA by traditional polymerase chain reaction (PCR) assay shouldn't be regarded as conclusive diagnostic basis. Instead, combined with mRNA and specific antigen detection, it is beneficial to improve the accuracy of diagnosis. Till now, the knowledge of human bocavirus remains poorly studied, which is deserved to further progress.
Infant ; Humans ; Child ; Child, Preschool ; Human bocavirus ; Climate ; Coinfection ; Epidemics ; Interferons

Different autoantibodies can be detected in patients with coronavirus disease 2019 (COVID-19). It is reported that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection could induce autoimmune diseases (AID), including children's multisystem inflammatory syndrome (MIS-C), Guillain Barre syndrome (GBS), Autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP) and thyroid autoimmune diseases. This article mainly reviews the similarities between COVID-19 and AID, the possibility of COVID-19 inducing AID, the risk of AID patients infected or vaccinated against COVID-19. The purpose is to provide strategies for the prevention, management and treatment of AID during the epidemic.
Child ; Humans ; COVID-19 ; SARS-CoV-2 ; Guillain-Barre Syndrome/therapy* ; Epidemics